Referencje:
Abstrakcyjny
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:scitldr/Abstract')
- Opis :
A new multi-target dataset of 5.4K TLDRs over 3.2K papers.
SCITLDR contains both author-written and expert-derived TLDRs,
where the latter are collected using a novel annotation protocol
that produces high-quality summaries while minimizing annotation burden.
- Licencja : Licencja Apache 2.0
- Wersja : 0.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 618 |
'train' | 1992 |
'validation' | 619 |
- Cechy :
{
"source": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"source_labels": {
"feature": {
"num_classes": 2,
"names": [
"non-oracle",
"oracle"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"rouge_scores": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"paper_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
AIC
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:scitldr/AIC')
- Opis :
A new multi-target dataset of 5.4K TLDRs over 3.2K papers.
SCITLDR contains both author-written and expert-derived TLDRs,
where the latter are collected using a novel annotation protocol
that produces high-quality summaries while minimizing annotation burden.
- Licencja : Licencja Apache 2.0
- Wersja : 0.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 618 |
'train' | 1992 |
'validation' | 619 |
- Cechy :
{
"source": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"source_labels": {
"feature": {
"num_classes": 2,
"names": [
0,
1
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"rouge_scores": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"paper_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"ic": {
"dtype": "bool_",
"id": null,
"_type": "Value"
},
"target": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
Pełny tekst
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:scitldr/FullText')
- Opis :
A new multi-target dataset of 5.4K TLDRs over 3.2K papers.
SCITLDR contains both author-written and expert-derived TLDRs,
where the latter are collected using a novel annotation protocol
that produces high-quality summaries while minimizing annotation burden.
- Licencja : Licencja Apache 2.0
- Wersja : 0.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 618 |
'train' | 1992 |
'validation' | 619 |
- Cechy :
{
"source": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"source_labels": {
"feature": {
"num_classes": 2,
"names": [
"non-oracle",
"oracle"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"rouge_scores": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"paper_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}